code: def decoder_for(args, odim, sos, eos, att, labeldist):
      """Return the decoding layer corresponding to the args.
  
      Args:
          args (Namespace): The program arguments.
          odim (int): The output dimension.
          sos (int): Number to indicate the start of sequences.
          eos (int) Number to indicate the end of sequences.
          att (Module):
              Attention module defined at `espnet.nets.chainer_backend.attentions`.
          labeldist (numpy.array): Distributed array of length od transcript.
  
      Returns:
          chainer.Chain: The decoder module.
  
      """
      return Decoder(
          args.eprojs,
          odim,
          args.dtype,
          args.dlayers,
          args.dunits,
          sos,
          eos,
          att,
          args.verbose,
          args.char_list,
          labeldist,
          args.lsm_weight,
          args.sampling_probability,
      )
  
file_path: espnet/espnet/nets/chainer_backend/rnn/decoders.py
imports: import logging
  import random
  from argparse import Namespace
  import chainer
  import chainer.functions
  import chainer.links
  import numpy
  import espnet.nets.chainer_backend.deterministic_embed_id
  from espnet.nets.ctc_prefix_score import CTCPrefixScore
  from espnet.nets.e2e_asr_common import end_detect
label_desc: Use image node_id 1 for calling a global function with example usage: decoder_for(args, odim, sos, eos, att, labeldist) and returns: Decoder